Book Image

Python Data Analysis - Second Edition

By : Ivan Idris
Book Image

Python Data Analysis - Second Edition

By: Ivan Idris

Overview of this book

Data analysis techniques generate useful insights from small and large volumes of data. Python, with its strong set of libraries, has become a popular platform to conduct various data analysis and predictive modeling tasks. With this book, you will learn how to process and manipulate data with Python for complex analysis and modeling. We learn data manipulations such as aggregating, concatenating, appending, cleaning, and handling missing values, with NumPy and Pandas. The book covers how to store and retrieve data from various data sources such as SQL and NoSQL, CSV fies, and HDF5. We learn how to visualize data using visualization libraries, along with advanced topics such as signal processing, time series, textual data analysis, machine learning, and social media analysis. The book covers a plethora of Python modules, such as matplotlib, statsmodels, scikit-learn, and NLTK. It also covers using Python with external environments such as R, Fortran, C/C++, and Boost libraries.
Table of Contents (22 chapters)
Python Data Analysis - Second Edition
Credits
About the Author
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface
Key Concepts
Online Resources

Analyzing word frequencies


The NLTK FreqDist class encapsulates a dictionary of words and counts for a given list of words. Load the Gutenberg text of Julius Caesar by William Shakespeare. Let's filter out the stopwords and punctuation:

punctuation = set(string.punctuation) 
filtered = [w.lower() for w in words if w.lower() not in sw and w.lower() not in punctuation] 

Create a FreqDist object and print the associated keys and values with the highest frequency:

fd = nltk.FreqDist(filtered) 
print("Words", fd.keys()[:5]) 
print("Counts", fd.values()[:5]) 

The keys and values are printed as follows:

Words ['d', 'caesar', 'brutus', 'bru', 'haue']
Counts [215, 190, 161, 153, 148]

The first word in this list is, of course, not an English word, so we may need to add the heuristic that words have a minimum of two characters. The NLTK FreqDist class allows dictionary-like access, but it also has convenience methods. Get the word with the highest frequency and related...